In radio frequency signal intercept applications, several highly desirable characteristics of the intercept receiver include broad band instantaneous frequency coverage, good sensitivity, good dynamic range, simultaneous signal detection, arbitration and parameter encoding, and fine frequency measurement. Further, in electronic warfare applications, the characteristics must be attainable with a goal toward minimal hardware and reduced signal processing speed.
The receiver architecture which covers most of these characteristics is the channelized receiver architecture. This channelized receiver comprises an antenna and a radio frequency front end which, respectively, intercept radio frequency energy and perform signal conditioning and down conversion to a convenient intermediate frequency. In order to widen a radio frequency bandwidth to improve the probability of intercept, the channelized receiver uses a number of contiguous filters, a filter bank, to sort the input signal into segments of predetermined frequency. An input signal with a certain frequency will fall into a certain filter. By measuring the output of the filters, the input signal frequency is estimated. The analog channelized receiver is expensive to fabricate because of the large number of filters required. Further, the receiver size is bulky and its maintenance is difficult because of the large number of components used.
Similarly, the digital form of a channelized receiver requires a contiguous set of digital band pass filters with linear phase that cover the intermediate frequency bandwidth. This coverage could be accomplished with a set of discrete digital filters; however, the digital filter bank can also be effectively implemented by performing the short time Fourier transform which in effect performs the discrete Fourier transform on weighted and overlapped partitions of a collection of discrete time signals. Using this approach, the short time Fourier transform complex modulates a low pass filter h(n) to form a uniform filter bank having one filter centered at each frequency bin of the fast Fourier transform. The low pass filter h(n) is, in effect, used to window the data. The established window slides across the data and then the discrete Fourier transform is calculated to give a frequency versus time output. Between successive fast Fourier transform calculations, M points are skipped which results in the output being decimated in time by M. It is also possible to generate a fine frequency digital channelized receiver by using an instantaneous frequency measurement algorithm. Such an instantaneous frequency measurement receiver uses the phase data generated by the short time Fourier transform filter bank to generate the fine frequency selection capability of the digital channelized receiver. The concept of a digital, channelized instantaneous frequency measurement receiver is known and is described in U.S. Pat. No. 5,499,391 by Tsui which is hereby incorporated herein by reference.
The digital channelized receiver, however, has limitations. The first limitation is caused by the structure of the filter bank and the pulsed nature of the input signals. In order to have continuous coverage across the instantaneous bandwidth, adjacent channel responses are overlapped to a large degree. In this respect, the channelized receiver acts like a spectrum analyzer. Thus, there is a great deal of crosstalk between the channels, even when the input is a simple continuous wave signal. This situation is exacerbated when a pulsed signal is input because the leading and trailing edges of the pulse contain a great deal of broad band energy which spills into adjacent and non-adjacent channels. The result is known as the "rabbit ear effect" because the out-of-channel, time-domain output responses have a peak on the leading and trailing edges of the pulse due to the impulse response of the filters. Due to these combined effects there is a second limitation; some method must be used to "arbitrate" between the filter channels and determine in which channel the input signal truly resides. The remaining responses are then classified as out-of-channel responses and discarded.
The frequency resolution capability or the ability to resolve and process two signals closely spaced in frequency, is limited by the receiver's arbitration capability. Currently, techniques such as amplitude comparison of adjacent channels and techniques that detect the presence of the "rabbit-ear" effect have been used to perform channel arbitration. Both of these approaches use only the amplitudes of filter bank outputs and have inherent limitations. Implementation of a known architecture, described by L. R. Rabiner and R. E. Crochiere in "Multi-Rate Digital Signal Processing", Prentis Hall, Englewood Cliffs, N.J., 1983, which could provide accurate arbitration capability, requires an inefficient number of decimators, expanders and polyphase filter components to be practical within the context of the digital receiver.